{"repo":"vaexio/vaex","free":true,"listed":false,"github":"https://github.com/vaexio/vaex","clone":"git clone https://github.com/vaexio/vaex.git","description":"Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀","language":"Python","stars":8509,"topics":["dataframe","python","bigdata","tabular-data","visualization","memory-mapped-file","hdf5","machine-learning","machinelearning","data-science"],"license":"MIT","category":"machine-learning","readme_excerpt":"What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion ( 10^9 ) samples/rows per second . Visualization is done using histograms , density plots and 3d volume rendering , allowing interactive exploration of big data. Vaex uses memory mapping, zero memory copy policy and lazy computations for best performance (no memory wasted). Installing With pip: Or conda: For more details, see the documentation Key features Instant opening of Huge data files (memory mapping) HDF5 and Apache Arrow supported. Read the documentation on how to efficiently convert your data from CSV files, Pandas DataFrames, or other sources. Lazy streaming from S3 supported in combination with memory mapping. Expression system Don't waste memory or time with feature engineering, we (lazily) transform your data when needed. Out-of-core DataFrame Filtering and evaluating expressions will not waste memory by making copies; the data is kept untouched on disk, and will be streamed only when needed. Delay the time before you need a cluster. Fast groupby / aggregations Vaex implements parallelized, highly performant groupby operations, especially when using categories ( 1 billion/second). Fast and efficient join Vaex doesn't copy/materialize the 'right' table when joining, saving gigabytes of mem","default_branch":null,"files":null,"tree":[],"storefront":"/r/vaexio","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/vaexio/vaex/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}